End-User Training: A Meta Model.

One of the major issues related to EUC is training individuals in colleges and in businesses to adopt to the new technology. This study is motivated by the issues created by end-user computing (EUC) and its growing importance within organizations. As a result, both researchers and practitioners are challenged to find new ways to train end users. Researchers have studied a number of key variables such as training support, delivery techniques, and individual differences that can be manipulated to enhance training program design in response to this challenge.

Massive investments in computing technology by universities and corporations and subsequent impact on return on investment, and the dynamic nature of information systems (IS) technology change cause a continual assessment of the management of IS. There is also a critical need for computer literacy and aptitude by all students and employees due to the pervasiveness of computers in the workplace. More specifically organizations are concerned about the long-term effect of training on individual performance. This study proposes an end-user training metamodel that organizations, trainers and researchers could use to devise effective training systems. This study reports the result of longitudinal study conducted in an industrial setting but relevant to other settings from higher education to private agencies and businesses.

Organizational needs and training methods are becoming more complex as organizations attempt to reengineer their administrative and production systems. End user training to meet these needs imposes an increase in the complexity and scope on training systems. The skills and knowledge workers need on the job are rapidly changing and require improvement in Training Systems. As a result, both industry managers and researchers are challenged to find new ways to train employees (Cabrales, Eddy, and Richards, 1992).

In response to this challenge, researchers have studied key variables such as training support, training delivery techniques, individual differences of the trainees, and technology that can be used to enhance effective training program design. The need for effective training programs and a variety of approaches to train and develop employees compete for organizational resources.

In order to achieve the maximum benefits of change, management must realize that workers are generally capable of performing above the level their jobs require or allow. In response, corporate interest in providing training in basic workplace skills has increased. For example, corporations such as Texas Instruments require their employees to take mandatory training in the job areas where they lack ability. Consequently, many corporations have opted to make rather than buy productive employees by investing in training programs (Tracey, 1985).

Problem

This study is motivated by the issues created by end-user computing (EUC) and its growing importance within organizations. One of the major issues related to EUC is training individuals to adapt to the new IT. Developing information systems (IS) human resources is ranked fourth and organizational learning and the use of IS technologies fifth among the top ten issues of IS management (Niederman, et al. 1991). The difference in training methodologies and job functions further complicates the training problem. For example, wordprocessors, spreadsheet, graphics, and other software packages are used throughout the organization, but the extent of their use varies depending on job functions. A clerk may use a word-processor more extensively than the manager, a manager may use spreadsheet software for decision-making functions, whereas a clerk may use it for data entry, and so on. Organizations face questions such as which is the most effective way of matching the workforces' requirements and the training methodology, what is an appropriate length of training for the variety of employees, and how much material is to be presented per training session (Cabrales and Eddy, 1992).

In addition to the problem created by existing IT, advances in IT create the need for human resources with specialized skills. The need for specialized skills means finding new, more productive training strategies. As a result, additional investments must be made (Irish 95). Management must look at more effective training and development strategies as a necessary investment. The key issue the management concerned about is how effective is a training method over a certain period of time. In summary, both researchers and practitioners agree that organizations should continually research effective ways of training employees to keep up with technological advances, especially when introducing software products that impact the entire corporation (Cabrales and Eddy 1992).

Overall, the problem addressed by this study is significant for the following reasons:

1. the critical need for computer literacy and aptitude due to the pervasiveness of computers in the workplace,

2. massive investments in computing technology by corporations and subsequent impact on return on investments,

3. and the ongoing nature of information technology (IT) change within the information systems (IS) domain.

This study addresses issues such as the impact of training delivery technique and type of computer application software on end user trainees' performance over an extended period of the training.

Proposed Training Model

In order to understand the impact of a training delivery technique it is logical to identify key variables and interaction between these variables. Developing a training model will help define the constructs from which key variables can be identified. A formal model will assist trainers and researchers to understand the impact of these variables on end users' performance. Training model also allows trainers to monitor and measure key variables. The measures of the key variables subsequently allow trainers to compare the variations of the training variables. Training model will also assist trainers to effectively design training systems. The authors propose the following training model. This model shows the basic elements of the End-User Training (EUT). These elements have been identified based on the analysis of the previous studies on training and development of individuals. Each element in Figure 1 is viewed as a contingent variable. The theoretical concepts use in analyzing these contingent variables are derived from studies in cognitive psychology (Norman 1983), human-computer interaction (Shneiderman 1982), educational psychology (Bloom 1956, Piaget 1974), and human performance (Newell and Simon 1972).

[Figure 1 ILLUSTRATION OMITTED]

Task Characteristics

Several studies have identified the influence of task characteristics on the human performance. Task characteristics refer to general properties of a task such as task type, task variety (e.g. hardware, software), complexity, difficulty, patterning, organization, identity, and type (Tsai 1991). Task analysis is critical in defining the content of a training program. Task analysis addresses several questions such as what tasks are performed, what should the trainees learn to perform these tasks, how should the trainees perform these tasks, what should the training module teach, and what should trainees learn for the actual job (Cabrales and Eddy, 1992).

Bloom (1956) developed a taxonomy of tasks for analyzing educational outcomes. It consists of six categories: knowledge, comprehension, application, analysis, synthesis, and evaluation. Each category requires certain behaviors to achieve its goals. Bloom's taxonomy implies that behaviors required by lower-level categories are required to perform the next higher-level behavior (Tsai 1991). This implies that a trainer may design a training effort depending on the task behavior required of an individual. For example, spreadsheet training may require more analytical type of skills than word-processor training may.

In the context of IS in general, understanding of the human-computer interface is a key to performing a task. So, there are two objectives to be achieved in training employees to perform a task: 1) training employees to provide actual understanding of task, and 2) training employees to use a computer interface or software (Cabrales, Eddy, and Richards, 1992).

Training Process

The training process is a function of factors such as, training method, content, tools, time, and trainer. Selection of these factors depends upon the trainee needs and task.

Training Method

There are various training methods used in training; such as Computer Based Training (CBT), Instructor Based Training (IBT), and one-on-one tutorials. Individual differences in learning require the use of a variety of training methods (Eddy and Spaulding, 1996).

Application of concepts such as cognitive models, user's conceptual models, and mental models are useful in the design and evaluation of training methods. The user conceptual model is a model typically formulated by a designer of a system to provide the user with a proper representation of that system. The training method influences model evolution in the mind of a user, representing the structure and internal relationships of a system as the user is learning and interacting with the system. Appropriateness of a specific training method depends on the mental model of the trainee. It is assumed that the trainee has formed a mental model of the system based on his or her prior experience with a similar system.

Training Tools

Selection of training tools depends upon several factors such as the trainer's ability to use the tool, the nature of its use in training, cost of the tool, and so on. Use of a computer as a teaching tool may enhance classroom learning, if used effectively. Use of tools such as a slide projector or video player for training are common in industry and in the classrooms.

Time and Content

It is logical to state that time and contents are mutually dependent. The amount of time available for training affects the nature and amount of content to be effectively presented during training. In the context of this study, time has two connotations, total training time and training time schedules. It does not include time spent in preparing a training program by the trainer.

Content, in general, refers to the material presented during the training process. Content may be presented in oral or written form through a delivery media (tools). Other contents are the training manuals provided to the employees for reference during and after the training. In the academic environment textbooks are provided to the students for reference (Spaulding and Eddy, 1996).

There are no studies that directly provide guidelines to a trainer to determine the training delivery time, content, and format in combination. However, conclusions of several studies on impact of time and presentation format on individuals performing a variety of tasks may be used as guidelines.

There is a strong dependence between the content covered during class and teaching method. For example, Leidner and Jarvenpaa (1993) found that in-class learning had procedural focus when computer-based methods were employed and a theoretical focus with traditional methods. In-class learning also depends upon how content is presented to the class. For example, Lusk and Kersnick (1979) measured the effect of presentation mode on learning and performance. Subjects in their experiment perceived tables to be less complex than graphs. However, Dickson, DeSanctis, and McBride (1986) found that the relationship between the presentation format and performance depends on task complexity. Hwang and Windsor (1990) also concluded that the effectiveness of presentation format depends on situational factors such as task complexity and time pressure.

Latham and Locke (1975) found that logging crews worked faster when deadlines were short. Bassett (1979.) found that individuals performed a simple clerical task faster when given shorter time limits. These studies suggest that an individual's familiarity with the task have direct impact on his or her productivity given a certain time period to complete that task. This implies that interaction between training time and individual's familiarity with the task or subject matter has an impact on his or her learning performance.

The results of these studies can explain the impact of time pressure on training effectiveness. For example, due to market demand and budget constraints on training time, time pressure is imposed on both the trainer and the trainees that may impact the outcome of the training. The nature of content depends upon the task, and trainer's ability to effectively present content in a format that is effective for trainees to grasp. The issue of information

overload is also relevant in this case. The question of how much processed information a trainer can deliver in a specified time depends upon human-memory capacity.

In a typical education environment, the time for training delivery varies depending upon the courses and the days of the week the courses are offered during the semester or quarter. However, in an industrial setting, due to market and financial constraints, the time for training delivery requires special consideration. There is a need to consider the impact of intermittent training on individual performance (Gattiker 1992). The factors that seem logical to consider in performing training-time analysis are task, content to be delivered, its format, and trainee characteristics.

In summary, the selection of time and content is contingent upon the overall circumstance of training requirements such as size of the class, schedule, time availability, and budget.

Trainer

Instructor factors such as teaching style, experience, ability to use computer-based tools during training process, and attitude influence the effectiveness of teaching. Instructor factors mediate the impact of the teaching methods on class interaction and in-class learning. Thus, trainer analysis is as important as trainee analysis. Trainer selection depends upon the complexity and the extent of training (Eddy, Burnett, Spaulding, and Murphy, 1997).

Trainee

The student or the trainee must be the focal point of training. Just as it is important to consider human-behavior in IS design and development, it is reasonable to include variations in human behavior among employees in an IS training program.

In addition, variations in human behavior are frequently expressed as individual differences. In lieu of formal definition of the term "individual differences" variations in human behavior among employees may be defined as individual differences including psychological factors (e.g., stress, learning, motivation), cognitive factors (e.g., cognitive style, cognitive process), and demographic factors (experience, education) (Tsai 1991). Individual differences among employees make the trainee a contingent factor.

In summary, the design of training programs requires trainee analysis, which includes the variations previously, discussed. Tracey (1985) suggests trainee selection as a part of the system validation that implies matching trainee's prerequisite knowledge for specific training episodes.

Outcome

Outcome refers to the increase in the performance of an individual as a result of training. The performance, in general, represents two components: quantitative performance referring to the efficiency and productivity, and qualitative performance referring to the increased satisfaction as a result of training. Both components are important for the overall organizational gain. Thus, the measure of the outcome determines the trainee's need for training and the training approach to be used in accomplishing the trainee's need.

Environment

Environmental factors impact both the internal training process and its outcome; and subsequently, learners are affected by environmental factors. Environmental factors are divided into in-class and workplace environments. The in-class environment includes physical factors such as lighting, room temperature, size, furniture, and layout. Other in-class factors may include number of trainees and the environment they create by their interaction (Eddy, Burnett, Spaulding, and Murphy, 1997).

The workplace environment includes conditions under which a trainee normally works or will work after the training. For example, a trainee may come from a workplace where he or she is working as a group member or independently. If working as a group member, it is possible that the trainee may receive assistance from another group member. In this situation, the trainee may simply need basic training. Alternatively, the trainee may need more training because he or she may not receive work group support (Eddy and Spaulding, 1996).

Other environmental issues are related to the organization climate or culture. Organizational climate is related to the management philosophy towards training employees for a specific job. For example, EDS has a separate training facility for training new employees for a specific job and training is mandatory. Texas Instruments allows its employees to seek training for a task when the employee believes he or she needs training to perform that task. Organizational climate also refers to the budget allocated for training. In summary, environment is an important consideration in designing a training program (Cabrales and Eddy, 1992).

Feild Experiment

In order to validate the proposed model a field experiment was conducted. Figure 2 shows the operational model used in the field experiment. Key variables studied were the training process, task characteristics, trainee, and outcome. Within training process we selected the training method and time schedule, within task characteristics we selected type and software, within trainee we selected demographic factors (education, experience), and within outcome we selected accuracy and satisfaction. The training methods used were instructor-based (IBT) training and computer-based training(CBT). Tasks selected for the study were Microsoft Word 6.0 and Excel 5.0. The target population for this study was endusers of information systems technology. The subjects (sample) for this study were employees of a Fortune 100 corporation located in a major southwestern city in the United States. The study included employees who were required to or who wanted to learn new software packages. Because of privacy and ethics concerns, the subjects' anonymity was preserved. The reason for using the corporate employees in the experiment was to strengthen the external validity of the study. It was assumed that the subjects selected for this study were all novices. Subjects were allowed to select training classes based on the training schedule provided by the training center. A self-selecting and convenience sample was employed in this study.

[Figure 2 ILLUSTRATION OMITTED]

Each subject was asked to sign a letter of consent stating that participating in the experiment is voluntary. Subjects could drop out of the experiment at any time they wished. Subjects were grouped in four groups - IBT (Word), IBT (Excel), CBT (Word), and CBT (Excel). IBT and CBT contents were similar and were designed to follow similar sequence of topics.

The IBT approach used a combined traditional training, stand-up lecture and the hands-on exploratory method. The CBT approach was similar to the IBT approach except for the absence of an instructor. CBT was a commercially available purchased software package and not custom developed for the experiment. CBT software for Microsoft Word (Ver. 6.0) and Excel (Ver. 5.0) were loaded on the computer system.

Findings

It is suggested by the findings that training significantly improve an individual's performance. The research also established that computer-based training (CBT) was more effective than instructor-based training (IBT) when pre-performance was not considered. However, IBT and CBT performances were not significantly different when pre-performance was considered. It was further determined that training schedule and its interaction with training method is significant for long-term retention.

The findings indicated that the major differences between IBT and CBT subjects attributed to the performance, enrollment for the classes, motivation and general attitude toward training method, and satisfaction with the facility. Motivation or attitude were not measured but interpreted based on the general comments made by the subjects and the proportion of IBT enrollment versus CBT enrollment. The CBT subjects' overall end-of-training and one-month-after-training performance was significantly better than IBT subjects were. This is consistent with the findings of Bohlen and Ferratt when they compared IBT with CBT (Bohlen and Ferrat, 1997).

It was observed during the research that the trainees in the CBT were found to have a high motivation to learn on their own and displayed a cooperative yet independent behavior. This finding concurs with Baxter (1993) which concluded that adult employees who are highly self-directed would experience greater success in self-paced instruction than those less self-directed. In follow-up discussions, the CBT subjects indicated that they preferred the flexibility CBT offers because they did not like to be bound by the classroom limitations and interruptions. Huang also found flexibility to be a key factor in the use of CBT (Huang, 1998). The demographic characteristics of IBT and CBT indicated that CBT subjects had a higher level of education and experience with computers. The percentage of CBT subjects with prior use of software was higher when compared with IBT subjects. On the other hand, in informal interviews the IBT subjects indicated that they preferred instructors because they could interact with the instructor whenever they needed assistance. A subject who tried to use CBT did not understand how to interact. Another subject came to CBT with an expectation that there would be an instructor to help. The subject did not know that CBT was a standalone software-training package. One CBT subject, with extensive computer experience, had difficulty interacting and understanding the instruction offered by the CBT software package. This implies that training managers need to critically evaluate the software interface while selecting CBT. In any case, the subject was successful in completing the training without any assistance.

These findings imply that even though CBT renders freedom to an individual during training, a difficult interface or instruction leads to frustration. CBT may enable more efficient interaction; interaction with the computer cannot be a substitute for human interaction (Leidner and Jarvenpaa 1995).

The lack of interaction in CBT impedes trainee clarification of ambiguous information presented. Since the goal of teaching or training is to promote the transfer of knowledge from instructor to trainee, any errors in comprehension lead to a partial knowledge transfer (Leidner and Jarvenpaa 1995). On the other hand, CBT alleviates the cognitive load of filtering training material and facilitates trainees to process information at their own pace (Leidner and Jarvenpaa 1995). In this research, CBT interaction was structured, although trainees could control their pace of training and spend various lengths of time on specific topics. This confirms Cole' s (1994) contention that CBT is not intended to completely replace the human instructor (Eddy and Spaulding, 1996).

It was determined by the research that CBT is an effective means of training; however, its acceptance as a formal training tool was not favorable. This conclusion was based on the total number of responses to the repeated announcement of CBT classes by the training department. Both IBT and CBT classes were announced; however, the CBT class enrollment was very low. This implies that training managers need to seek alternate ways to encourage end-users to take CBT to acquire the cost savings over IBT. Goodwin and Rees (1995) state that changes in perceptions of users regarding CBT may increase their use of CBT. This will require a special effort on part of management to educate users about the importance of CBT as a training tool. Educating users about the possible cost advantage of CBT over IBT may also motivate users to increase the use of CBT.

Another implication of this research for training managers concerns the long-term learning effect of training. A one-month follow-up questionnaire used by the authors indicated that a majority of the end-users did not use the target software during the month after the training. Not using the training material after training suggests an overhead expense that would not be effectively utilized. If corporate leaders can correctly identify the employees who need training and who would apply the training immediately, then the result would be a cost savings by not training the employees who do not have a need to use the training material (Eddy and Spaulding, 1996).

A further implication for training managers concerns the type of CBT used for training. Training managers may have to work closely with the CBT vendors or designers and determine the parameters critical to end-users in effectively using the CBT.

The study found no significant difference between Microsoft Word (Ver. 6.0) and Excel (Ver. 5.0) subjects' performance at the end-of-training. The demographic data about the current use of the software revealed that a greater number of Excel subjects had used the software before training compared to Microsoft Word subjects, i.e., the current use of a software complements training effectiveness. The subjects expressed indifferent feelings about satisfaction with the training.

This study demonstrated that the training was more effective in long-term retention effect for the subjects in the Excel course than for the subjects in the Microsoft Word course. This was because a larger number of Excel subjects had used Excel during the one-month-after training period than Microsoft Word subjects.

The nature of the task and frequency of use is also critical in determining performance (Cabrales and Eddy, 1992). For example, Morrison and Witmer (1983) compared computer-based and print-based job performance aids and found that on the first trial, computer-based aids produced more accurate performance on the simpler tasks, whereas print-based job performance was better on the complex tasks. However, on subsequent trials there was no difference in performance. An easy task elicits better performance from novice learners than complex tasks, and computer-based attitudes of novice learners operate to affect their performance (Jackson, Vollmer, and Stuurman 1985). This implies that it is the frequency of use of training material after the training that determines the long-term learning retention of a task (Eddy, Burnett, Spaulding, and Murphy, 1997).

The results of this study further indicated that the interaction effect of a training method and training task is significant both for performance accuracy and for user satisfaction. This implies that interaction of training method and tasks should be considered when long-term learning retention is desired. Task complexity and its relation to cognitive processing has been addressed by previous studies (e.g., Tsai 1991). Thus, a CBT interface for specific software that complements the cognitive processing ability of an individual will facilitate learning retention.

Conclusion

A specific model and a strategy have been presented. The elements are: the task characteristics, the training process, the trainee, the outcome, and the environment. These elements are in constant interaction. The extent of interaction varies with each training instance. The research shows that there is a significant difference in an individual's performance accuracy depending upon the training method used. A key issue the research identified was that it is difficult to sell the CBT method as a formal training tool to the employees. The research in this study further revealed that if trainees practiced what is learned in the class after the training, they would have a long-term retention of training. The training task, specifically the application of software packages, was found to be significant. Their interaction with training method was even more significant than training method or tasks themselves.

This model/strategy will allow companies to develop sound training program for the 21st century (Cabrales, Eddy, and Richards, 1992). It is anticipated that conducting future research as recommended in this study would result in more complete findings into the effective approach to training end-users.

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Mayur S. Desai, Indiana University - Kokomo. Thomas Richards and John Paul Eddy, Universtiy of North Texas.

Correspondence concerning this article should be addressed to Dr. Mayur S. Desai, Assistant Professor, Division of Business and Economics, Indiana University, PO Box 9003, Kokomo, Indiana 46904-9003.

(*) This paper is based on a dissertation by the first coauthor. He would like to express his appreciation to his dissertation chair, Dr. J. Wayne Spence, University of North Texas.